With big data, the DNC turns politics into political science

The next edition of the HP Discover Performance Podcast Series focuses on the big-data problem in the realm of politics. We’ll learn how the Democratic National Committee (DNC) leveraged big data analytics to better understand and predict voter behavior and alliances in the 2012 U.S. national elections.

To learn more about how the DNC pulled vast amounts of data together to predict and understand voter preferences and positions on the issues, join Chris Wegrzyn, Director of Data Architecture at the DNC, based in Washington, DC.

The discussion, which took place at the recent HP Vertica Big Data Conference in Boston, is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions. [Disclosure: HP is a sponsor of BriefingsDirect podcasts.]